Regime switching in yield structures and forecasting securitised real estate returns

The predictability of real estate returns has been a subject of significant examination by real estate research. Several studies have found that real estate returns are predictable suggesting the existence of profitable trading opportunities. Empirical linear and non-linear methods have been employed, which use a number of series as predictors including interest rates and their differentials, dividend yields and inflation. The present study extends the existing work and focuses on the structure of yields between broad asset classes (real estate, equities and government bonds) and the implications for portfolio allocation decisions and real estate investment. It is based on the premise that investment asset markets are integrated and that differentials in the yields on assets trigger switching of funds among asset classes. Therefore we investigate the claim that the yield ratios of indirect to direct real estate and of real estate to equities or bonds contain useful information for determining the likely direction of future real estate returns. A Markov switching regime approach is deployed to allow for different states in yield differentials. The Markov model identifies distinct regimes for the yield ratios of indirect to direct real estate, indirect real estate to equities and direct real estate to gilts. Trading rules are developed based on the filtered Ò real time Ò probabilities of the regime switching models. It is observed that the regime switching trading rules generate a superior risk-return profile than simple buy-and-hold strategies.